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Model-to-Clinic, RFA-RM-27-013, is the translational arm of the NIH Common Fund's PRIMED-AI programme. It funds teams to take AI-enabled, image-based multimodal clinical decision support models and move them toward actual use in clinical settings, addressing the gap that has defined clinical AI for a decade: models that perform well retrospectively and then fail to change practice.
The award uses a two-phase UG3/UH3 cooperative agreement, with a milestone-gated preparatory phase capped at 450,000 US dollars in direct costs per year followed, on successful transition, by a phase capped at 1,000,000 US dollars in direct costs.
Clinical trials are optional, so teams can pursue prospective evaluation or focus on workflow integration, interoperability and clinician-facing deployment without being forced into a trial design.
PRIMED-AI deliberately splits the pipeline across five opportunities, and M2C sits downstream of the Data-to-Model academic-industrial partnerships and alongside an independent Validation Center that will evaluate tools the programme produces, so successful applicants should expect their models to be externally scrutinised rather than self-assessed. The RFA was released on 30 June 2026 with applications due 19 October 2026.
For academic medical centres with both AI development capability and real clinical implementation reach, this is one of the few federal mechanisms that pays specifically for the translation step rather than treating it as dissemination.
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Or search similar grants →According to the current listing, eligibility includes: Standard NIH eligibility applies across United States higher education institutions, non-profit research organisations, for-profit entities, hospitals and government organisations, with the realistic applicant being an academic medical centre or health system with paired AI development and clinical implementation capacity. The defining requirement is access to a clinical setting in which the tool can plausibly be deployed, since the mechanism funds translation rather than model development; teams holding a strong model but no clinical partner should secure one before applying or consider the Data-to-Model opportunity instead. The UG3/UH3 structure imposes a specific planning obligation: applicants must propose explicit, assessable milestones for the UG3 phase, and NIH will gate the transition to the larger UH3 phase on whether those milestones are met, so milestone design is a substantive part of the application rather than administrative detail. As a cooperative agreement, the award carries substantial NIH programmatic involvement and a requirement to coordinate with the PRIMED-AI Logistics Center, Validation Center and other awardees. Clinical trials are optional, which means proposals involving prospective human-subjects evaluation must include the relevant regulatory, IRB and data-monitoring plans and absorb their cost within the published ceilings. Applications are due 19 October 2026 following release on 30 June 2026, submitted via Grants.gov. The full RFA in the NIH Guide governs over any summary and should be read in detail, particularly the milestone and transition provisions. Confirm the full requirements in the official notice before applying.
The current listing shows budgets are capped by phase: applicants may not exceed 450,000 US dollars in direct costs per year for the UG3 phase and 1,000,000 US dollars in direct costs for the UH3 phase, so amount_min is recorded as 450,000 and amount_max as 1,000,000. Both are direct-cost ceilings, which means the total cost to NIH is materially higher once facilities and administrative costs are added, and applicants at institutions with high indirect rates should model total project cost rather than the headline figure. The two-phase UG3/UH3 structure is the operative constraint on planning. The UG3 phase is a milestone-driven preparatory period and the transition to UH3 is not automatic: NIH assesses whether pre-specified milestones were met before releasing the larger phase. A proposal therefore needs milestones that are both meaningful and genuinely achievable inside a 450,000-dollar-per-year envelope, because over-ambitious UG3 milestones are a common cause of failed transitions. For the UH3 phase, 1,000,000 dollars in direct costs is substantial for a translational informatics project but tight for anything involving prospective clinical workflow integration across multiple sites, so applicants should be realistic about site counts. Clinical trials are optional under this mechanism, which gives flexibility but also means a proposal involving human-subjects clinical evaluation must carry the associated regulatory and monitoring costs within the same ceiling. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NIH Common Fund PRIMED-AI Model-to-Clinic (M2C) RFA-RM-27-013 UG3/UH3 for Translating AI Imaging Clinical Decision Support Tools into Clinical Practice are due October 19, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NIH Common Fund PRIMED-AI Model-to-Clinic (M2C) RFA-RM-27-013 UG3/UH3 for Translating AI Imaging Clinical Decision Support Tools into Clinical Practice is funded by U.S. National Institutes of Health (NIH) Common Fund, Office of Strategic Coordination. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.
PRIMED-AI is a new NIH Common Fund programme, Precision Medicine with AI: Integrating Imaging with Multimodal Data, which combines medical imaging with other health data to build AI-powered clinical decision support tools for personalised medicine. This opportunity, RFA-RM-27-014, funds the programme's Validation Center: a dedicated hub that independently evaluates and characterises the AI-enabled, image-based multimodal clinical decision support tools developed elsewhere in the consortium. The structural logic matters for applicants. NIH has separated tool-building from tool-validation and is paying separately for the second, which signals institutional recognition that self-reported performance claims from developing teams are not sufficient evidence for clinical AI. The Center's remit covers verification, validation, interoperability and uncertainty quantification, so the deliverable is a reproducible evaluation capability rather than a set of papers. It operates as a U54 cooperative agreement, meaning NIH staff are substantively involved and the Center must work in concert with the PRIMED-AI Logistics Center and the Data-to-Model and Model-to-Clinic award recipients. The RFA was released on 30 June 2026 with applications due 2 October 2026. For academic groups that have built credible AI evaluation methodology, particularly in radiology, imaging informatics or biostatistics, this is an unusually direct route to becoming the reference evaluator for a major federal AI health programme, and the position carries influence over how clinical AI performance gets measured well beyond the life of the award.
RFA-RM-27-015 funds a single Logistics Center as the coordinating hub of the NIH Common Fund's PRIMED-AI program, Precision Medicine with AI: Integrating Imaging with Multimodal Data. The award is a cooperative agreement, meaning substantial NIH scientific and programmatic involvement is built in rather than incidental, and it is administered by NIBIB on behalf of the Common Fund. The Center operates through three integrated cores: Administration, which runs the steering committees and develops consortium policies; Evaluation, which assesses progress across the funded portfolio; and Outreach, which maintains a web portal for sharing AI-based clinical decision support tools and facilitates engagement between researchers, clinicians and patient communities. The strategic point for applicants is that this is the only coordinating award in a multi-award program whose other components, the Data-to-Model Academic-Industrial Partnerships, Model-to-Clinic and Multi-use Frameworks Playbook RFAs, are separately competed and separately funded. The Logistics Center therefore does not generate its own AI models; it is scored on its capacity to run a consortium, set data and tool-sharing policy, and build infrastructure that makes other teams' clinical decision support tools discoverable and reusable. Applications are due by 5:00 PM local time of the applicant organization on the date specified for the relevant review cycle, with an earliest project start date of 2 October 2026 and a maximum project period of five years.
NOT-RM-26-004 asks the public for NIH-wide research challenges worth a 10-year, cross-institute program. There is no budget, no biosketch, no page limit, and no award. What there is: the five criteria every Common Fund investment has met since 2006, a new bullet about small-lab burden, and a fund whose FY 2026 request came in at $347.4 million — down 49.3 percent.
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Read articleThe NIH Common Fund launched PRIMED-AI — Precision Medicine with AI: Integrating Imaging with Multimodal Data — as five coordinated funding opportunities (RFA-RM-27-011 through -015) that build a full pipeline from standards to clinic. Here is how the Playbook, Data-to-Model partnerships, Model-to-Clinic translation, Validation Center, and Logistics Center fit together, what each pays, who is eligible, and how to position before the October 2026 deadlines.
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